[jira] [Assigned] (SPARK-30178) RobustScaler support bigger numFeatures

["zhengruifeng (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-30178?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

zhengruifeng reassigned SPARK-30178:
------------------------------------

    Assignee: zhengruifeng

> RobustScaler support bigger numFeatures
> ---------------------------------------
>
>                 Key: SPARK-30178
>                 URL: https://issues.apache.org/jira/browse/SPARK-30178
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 3.0.0
>            Reporter: zhengruifeng
>            Assignee: zhengruifeng
>            Priority: Minor
>
> It is a bottleneck to collect the whole Array[QuantileSummaries] from executors,
> since a QuantileSummaries is a large object, which maintains large arrays of size 10k({color:#93a6f5}defaultCompressThreshold{color})/50k({color:#93a6f5}defaultHeadSize{color}).
> So we need to compute the ranges/medians more distributedly.
> In Spark-Shell with default params, I processed dataset with numFeatures=69,200, and current impl fail due to OOM.



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